A Multi-Agent System for Remanufacturing of End-of-Life Products

Abstract:

Efficient remanufacturing of end-of-life (EOL) products is crucial for environment friendly production. Disassembly is part of the remanufacturing and it is meant to obtain components and materials from end-of-life products. An essential performance objective of a disassembly process is the benefits it brings, that is the revenue brought by the retrieved parts and material, diminished by the cost of their retrieval operations. A decision must be taken to balance the disassembly production system. In this paper, a multi-agent system (MAS) is presented to optimize the remanufacturing process of EOL products. The MAS offers a synthesized information platform for various tasks, e.g. product/manufacturing information processing, disassembly sequencing, solution performance assessing, and processes scheduling. On one hand, the MAS could retrieve much information related design/manufacturing resources, by multi-level data obtaining mechanism. On the other hand, this information will make the prospective integrated environment for profitable remanufacturing system planning more feasible.

• Periodical: Advanced Materials Research (Volumes 655-657)
• Pages: 2025-2032
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.655-657.2025
• Online since: January 2013
• Authors: Xiao Qiang Shi, Li Jiang Huang, Hui Wang
• Keywords: Disassembly, Multi-Agent System (MAS), Optimization, Remanufacturing

References

[1] M. Wooldridge and N. R. Jennings: Knowledge Engineering Review, Vol. 10(2), (1995), pp.115-152.

[2] D. Srinivasan, M. C. Choy: IEE Proceedings of Intelligent Transport Systems, Vol. 153(1),  (2006), pp.41-50.

[3] Wang hui, Xiang Dong, Duan Guanghong: The Proceedings of 1st IEEE International Conference on Engineering Intelligent Systems, (2006), pp.447-451.

DOI: 10.1109/iceis.2006.1703209

[4] WANG Hui, XIANG Dong, DUAN Guanghong: Neurocomputing. Vol. 71(13-15), (2008), pp.2720-2726.

DOI: 10.1016/j.neucom.2007.11.042

[5] Mitsuo Gen, Runwei Cheng: Genetic Algorithm and Engineering Optimization, (John Wiley & Sons, Inc., 2000).

[6] Lawrence Davis: Handbook of Genetic Algorithms, (Van Nostrand Reinhold, USA, 1991).

[7] Wang Hui, Xiang Dong, Duan Guanghong: The Proceedings of 12th CIRP Life Cycle Engineering Seminar, (2005).

[8] Takeshi Yamada, Ryohei Nakano: The Proceedings of 2nd International Conference on Parallel Problem Solving from Nature (PPSN), (1992), pp.281-290.

[9] Luminita Duta, Florin Gheorghe Filip, Jean-Michel Henrioud, Ciprian Popescu: Int. J. of Computers, Communications & Control, Vol. 3, (2008), pp.270-280.

[10] Seamus M. McGovern, Surendra M. Gupta: European Journal of Operational Research, Vol. 179(3), (2007), pp.692-708.

[11] Seamus M. McGovern and Surendra M. Gupta: Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing IV, (2004), pp.53-66.